Retail 101

As MakerSights grows at a good clip, the team continues to prioritize an even split of talent between technical/engineering expertise and customer facing skill sets with prior retail industry experience. One customer facing workforce (comprised of sales + strategic engagement teams) has some impressive experience with brands and retailers including Neiman Marcus, Amazon, Bloomingdale’s, Birchbox, A&F, and more. We’ve recognized early on as a fast paced customer-centric company the overall importance of having our entire team privy to the day-to-day lives of our core customers, and ultimately prioritizing the the cross-functional sharing of knowledge.

To that end, we recently took a few hours away from the office to deep-dive our customers -- how they win, how they struggle, and how we can help them improve their bottom lines and overall daily job satisfaction!  It was interesting to come away from our offsite with a plan for building out our relationships with current partners coming from the perspectives of both our retail experts + our software engineers. Here’s some of what we learned:

• There are actually dozens of decision points where MakerSights can help brands make faster, better decisions outside of early stage product development, initial line review, and go-to-market meetings! Every team’s needs are different, and we walked through a few examples to illustrate how opportunities to leverage data can come from both calendarized processes and ad-hoc business questions. For example:
• A sourcing team may need to quickly re-evaluate the line to see if styles that aren’t reaching factory minimums should be dropped
• A design team may not agree on logo placement, delaying production, and would benefit from structured feedback from the customer
• A planning team finds that margins on an assortment look tight, and is looking for opportunity in styles that they can increase retail price without sacrificing volume.
• Although widely known that the product development process should move faster and more efficiently, but complexity and global production make this a huge challenge. Data science is not just improving the decision-making process, it’s improving their speed to market as well! We love this article that goes into how Nike and H&M build up their supply chains.
• Brands want to understand their customers better - seasonless style, online shopping, and social media are changing the calendar and the way we shop. Understanding the customer becomes the key to responsiveness by creating supply only where there is demand. Read here on how Micky Drexler learned the hard way that fashion has changed from a supply driven market to a demand driven one.
• Brands and retailers want to ask the right questions to the right audiences to get actionable insights to support many gut-based decisions. Data science has the power to enable scale, while also delivering personalization. Katrina Lake talks about this here.